The Effect of Physical Height on Workplace Success and Income:
Preliminary Test of a Theoretical Model
Timothy A. Judge
University of Florida
Daniel M. Cable
University of North Carolina
In this article, the authors propose a theoretical model of the relationship between physical height and
career success. We then test several linkages in the model based on a meta-analysis of the literature, with
results indicating that physical height is significantly related to measures of social esteem (? ˆ ? .41),
leader emergence (? ˆ ? .24), and performance (? ˆ ? .18). Height was somewhat more strongly related to
success for men (? ˆ ? .29) than for women (? ˆ ? .21), although this difference was not significant. Finally,
given that almost no research has examined the relationship between individuals’ physical height and
their incomes, we present four large-sample studies (total N ? 8,590) showing that height is positively
related to income (?ˆ? .26) after controlling for sex, age, and weight. Overall, this article presents the
most comprehensive analysis of the relationship of height to workplace success to date, and the results
suggest that tall individuals have advantages in several important aspects of their careers and organiza-
“Short people got no reason, to live.”
—Randy Newman, Short People1
“I feel as tall as you.”—Ellis Meredith, U.S. suffragist
There seems to be a societal impression that taller people are
more successful in life. Although it is tempting to dismiss this
belief as a folk tale, research suggests that some elements of life
are easier for taller people because height is a socially desirable
asset (Roberts & Herman, 1986). For example, taller individuals
are judged as being more persuasive (Young & French, 1996),
more attractive as mates (Freedman, 1979; Harrison & Saeed,
1977; Lerner & Moore, 1974), and more likely to emerge as a
leader of other people (Higham & Carment, 1992; Stogdill, 1948).
Indeed, on the latter point, not since 1896 have U.S. citizens
elected a President whose height was below average; William
McKinley at 5 ft 7 in. (1.7 m) was ridiculed in the press as a “little
Theoretically, the importance of height has evolutionary origins,
because animals use height as an index for power and strength
when making fight-or-flight decisions. As noted by Freedman
(1979), “Throughout nature the rule is the bigger, the more dan-
gerous” (p. 92). Thus, from a sociobiological perspective, height
equals power and therefore demands respect. Perhaps due to the
close linkage between height and social power, there also appears
to be a psychology of stature whereby people’s height has far-
reaching consequences on their dispositions, personalities, and
behaviors. In fact, Alfred Adler coined the phrase Napoleon com-
plex to describe cases when peoples’ short stature makes them feel
inadequate, leading to an inferiority complex and the adoption of
overaggressive behavior to compensate for lack of height and
power (Adler, 1956; Martel & Biller, 1987).
Height should be particularly relevant in the workplace where
issues of persuasion and power take on special significance. Some
evidence exists for this position, because many employers seem to
believe that height and workplace success are linked. For example,
Kurtz (1969) found that the majority of recruiters (78%) believed
that salespersons of above average height were more impressive to
customers than shorter salespersons. Lester and Sheehan (1980)
found that supervisors expected short police officers to receive
more complaints, cause more disciplinary problems, and engender
poorer morale than taller police officers. In the context of aca-
demia, Hensley (1993) noted, “The perception seems to exist that
taller individuals are somehow more capable, able, or competent”
(p. 40). Moreover, as suggested previously, some qualitative re-
views have suggested positive relationships of height with perfor-
mance, leader effectiveness, and leader emergence (see Hensley &
Cooper, 1987; Roberts & Herman, 1986).
To develop the literature on height and workplace success, the
present study has three goals. First, although some past research
has suggested interesting linkages between physical height and
measures of career success, no conceptual model has been pro-
posed to articulate why or how this linkage exists. Accordingly, we
first address the atheoretical nature of the existing literature by
1The song brought Newman accusations of the very injustice he was
satirizing, and in Maryland it remains illegal for radio stations to air the
Timothy A. Judge, Department of Management, Warrington College of
Business, University of Florida; Daniel M. Cable, Kenan-Flagler Business
School, University of North Carolina.
We thank John D. Kammeyer-Mueller for his comments and insights on
the article and the theoretical model.
Correspondence concerning this article should be addressed to Timothy
A. Judge, Department of Management, Warrington College of Business,
University of Florida, 211D Stuzin Hall, P.O. Box 117165, Gainesville, FL
32611. E-mail: firstname.lastname@example.org
Journal of Applied Psychology
2004, Vol. 89, No. 3, 428–441
Copyright 2004 by the American Psychological Association
0021-9010/04/$12.00 DOI: 10.1037/0021-9010.89.3.428
proposing a process model of the height–career success
Next, we conduct a meta-analysis of the height–workplace suc-
cess literature to test some of the general implications of the
process model. There has not been a comprehensive attempt to
assess the general trend of findings across the height–career suc-
cess studies that have accumulated over the past 75 years. Thus,
research on height and workplace success has been conducted in
many different methodological contexts across many different
outcomes, and no attempt has been made to assess the robustness
of the effects across investigations. In addition to showing the
general strength and variability of relationships, a statistical ex-
amination of past research is valuable because trends in research
are difficult to interpret qualitatively. For example, after reviewing
both positive and null relationships in their review of the literature,
Roberts and Herman (1986) noted, “The evidence to support or
contradict the existence of systematic prejudices against tall or
short individuals remains inconsistent” (p. 134).
Finally, we conduct four new investigations of the relationship
between individuals’ height and their personal incomes. Although
income is the most common index of career success (e.g., Judge,
Cable, Boudreau, & Bretz, 1995; Whitely, Dougherty, & Dreher,
1991), almost no research has examined how height affects income
levels. If tall people are in greater demand and less supply than
average-sized people, then firms should be willing to pay more to
get them. However, only three published articles have empirically
examined this hypothesis (Deck, 1968; Frieze, Olson, & Good,
1990; Melamed, 1994); because participants in these existing
studies reported both their salaries and height at the same time, it
is possible that people exaggerated both their income and their
height (Roberts & Herman, 1986). Moreover, existing research on
the height–income relationship has been confined to the hiring
context, and researchers have suggested that this relationship
should disappear once managers have the opportunity to observe
true performance (Hensley & Cooper, 1987). In this article, we
conduct four investigations of the height–income linkage across
the course of individuals’ careers, using measures of height and
income that are either longitudinal or independently reported.
THEORETICAL MODEL OF PHYSICAL HEIGHT
AND CAREER SUCCESS
Figure 1 displays the hypothesized model that links height and
career success. Consistent with past research, we conceptualize
career success as the outcomes or achievements one has accumu-
lated as a result of one’s work, measured by earnings (i.e., com-
pensation) and ascendancy into leadership positions (e.g., Gattiker
& Larwood, 1988; Judge et al., 1995; Whitely et al., 1991). In
general, the model suggests that height affects career success
through several mediating processes. First, height affects how
individuals regard themselves (self-esteem) and how individuals
are regarded by others (social esteem). Next, social esteem and
self-esteem affect individuals’ job performance as well as how
supervisors evaluate their job performance, which in turn affects
success in their careers. In the following discussion, we review the
conceptual and empirical evidence for each linkage in the model.
Then, we propose several general hypotheses that emerge from the
model that we test with a meta-analysis and four investigations of
the height–income relationship. Because our purpose here is
theory-building, we should note that the empirical portion of our
study is not intended as a complete test of our proposed model.
Rather, we test various relationships that are either directly sug-
gested by the model or implied by the model.
By social esteem, we refer to how positively one is evaluated or
regarded by others in society, which has been operationalized in
past height research as “perceived stature,” “perceived esteem,”
and “ascribed status” (e.g., Hensley, 1993; Kurtz, 1969; Lechelt,
1975; Wilson, 1968). As noted in the introduction, sociobiologists
suggest that it was evolutionarily advantageous for creatures to
interpret height as power (Freedman, 1979). Perhaps for this
reason, both visual perception and social norms have developed
around the meaning of size and height.
In terms of visual perception, research reveals a basic human
perceptual bias whereby people expect a positive relationship
between an entity’s size and its value or status (Dannenmaier &
Thumin, 1964; Higham & Carment, 1992; Lechelt, 1975). Thus,
studies have shown that people perceive more valuable things as
larger than less valuable things; for example, coins are perceived
as larger than cardboard disks of identical diameter (Bruner &
Goodman, 1947), and jars filled with candy are judged to be
heavier than jars of equal weight filled with sand (Dukes & Bevan,
1952). This perceptual bias also extends to judgments about peo-
ple’s height and the extent to which they are esteemed by others.
A number of studies have shown that the prestige of a person’s
occupation affects judgments about his or her height and that
presidential candidates who win are seen as being taller than their
opponents who lose (Dannenmaier & Thumin, 1964; Hensley &
Angoli, 1980; Lechelt, 1975; Wilson, 1968). For example, a study
of Canadian voters revealed that, after the 1988 Canadian federal
Theoretical model of the height–career success relationship.
EFFECT OF PHYSICAL HEIGHT
election, voters judged the winner (Brian Mulroney) to be taller
than before the election and judged the losers to be shorter than
before the election (Higham & Carment, 1992).
In terms of social norms, height has long been a metaphor for
importance and power (Roberts & Herman, 1986, p. 115) and is
often used as a “heuristic for dominance” (Young & French, 1998,
p. 321). Thus, individuals seem to hold taller people in higher
esteem than shorter people and are more likely to be convinced and
persuaded by tall people than short people (Baker & Redding,
1962; Zebrowitz, 1994). Language also helps reveal the social
value of height (Hensley & Cooper, 1987). When a person is
highly esteemed, he may be described as a “big man,” and we
“look up” to and admire those who are tall (Frieze et al., 1990, p.
47; Hensley & Angoli, 1980). Thus, as shown in the model, the
first process that links height to career success is the esteem in
which others hold tall individuals.
In addition to influencing how others perceive us, height also
may affect how we regard ourselves.2Studies show that physical
appearance has a bearing on individuals’ psychological adjustment
(DelRosario, Brines, & Coleman, 1984) and is one of the best
correlates of self-esteem (Locke, McClear, & Knight, 1996). As
noted earlier, physical height is linked with social power and
respect, and therefore short people may become dissatisfied with
their physical stature (Adler, 1956; Martel & Biller, 1987). Across
time, individuals’ insecurities about their height may lead to per-
sonalities that reflect their stature, perhaps even resulting in ag-
gressiveness and arrogance that serve as compensatory mecha-
nisms (Adler, 1956). Also, as suggested by the linkage in Figure 1
between social esteem and self-esteem, people are not immune to
how others view them, and people tend to take on the attributes
that society ascribes to them (Jones, 1977). Accordingly, tall
individuals may develop greater feelings of self-worth and self-
confidence, because they are consistently viewed and treated with
respect by others; this becomes a self-fulfilling prophecy (Roberts
& Herman, 1986). Although little empirical research has examined
the link between height and self-esteem (Martel & Biller, 1987),
Hood (1963) found that short males scored slightly but signifi-
cantly higher than tall males on the inferiority and depression
scales of the Minnesota Multiphasic Personality Inventory, and
Adams (1980) found that height was positively associated with
external locus of control and emotional reactivity.
As indicated in the model, we expect the esteem in which others
hold an individual to affect that individuals’ job performance. In
this article, we examine two types of job performance: objective
performance (i.e., job or task outcomes and results) and subjective
performance (i.e., how others such as managers evaluate perfor-
mance). On one hand, this distinction is very useful because it is
important to determine if height simply alters others’ perceptions
of individuals (leading to more favorable subjective ratings) or if
taller people are in fact better performers according to objective
criteria. On the other hand, the distinction between objective and
subjective job performance may be much clearer in theory than in
reality. For example, sales revenues may seem to be an objective
performance measure, but in many cases it depends on subjective
appraisals such as who gets the best sales leads, who generates the
most favorable customer reactions, and so forth. Thus, in the
present article, we examine subjective and objective job perfor-
mance separately but offer the caveat that the distinction may not
be unambiguous for many jobs.
Theoretically, the esteem in which a person is held by others can
lead to objective performance, particularly in positions where
social interaction is important. For example, customers may expe-
rience greater admiration or respect for tall people during interac-
tions and therefore may be more likely to buy from a tall sales-
person (Kurtz, 1969). Likewise, people who are admired or held in
esteem may be more able to develop trust, acquire information, or
negotiate with others more effectively. Thus, an individual’s social
power and stature may create a self-fulfilling process: esteemed
people are more able to deliver job results that make them even
more esteemed (Dipboye, 1982; Roberts & Herman, 1986).
The esteem in which others hold a person should be even more
likely to affect subjective performance than objective performance.
First, others’ esteem for an individual can indirectly affect man-
agers’ subjective job evaluations because, as described previously,
social esteem can affect the actual job results that are produced by
the individual. Naturally, job results affect managers’ performance
appraisals. However, regardless of actual performance levels, so-
cial esteem and respect also can create expectations in individuals’
managers that lead to biased hypothesis testing (Snyder & Cantor,
1979), thus resulting in a self-fulfilling process (Merton, 1948). In
other words, managers may factor their initial beliefs about em-
ployees into their subjective appraisals of performance (Dipboye,
1982; Roberts & Herman, 1986), thereby “causing” the relation-
ships they expected.
Figure 1 shows that we also expect self-esteem to mediate the
link between height and performance. Self-esteem, confidence,
and poise are assets on most jobs and lead to enhanced job
performance (Erez & Judge, 2001). Moreover, even after control-
ling for actual productivity, we expect individuals with positive
self-esteem to have higher performance ratings because “self-
positive” individuals are viewed more favorably and are better
liked (Judge, Erez, & Bono, 1998). Thus, we predict that self-
esteem is positively related to managers’ performance ratings
(Judge & Bono, 2001).
The final stage in the model links employees’ objective and
subjective performance to their earnings and career success. Given
2Whereas social esteem could be considered to be synonymous with
stature (stature being defined as a quality or status that is associated with
height), self-esteem is a concept regarded by many as a trait (Neiss,
Sedikides, & Stevenson, 2002). For example, research on core self-
evaluations views self-esteem as an indicator of a higher order trait (Judge,
Erez, Bono, & Thoresen, 2002). For our purposes, we view self-esteem as
a broad concept that has a stable trait component (owing to genetic
influences) but also is susceptible to environmental influences, as is the
case when one’s height influences appraisals of one’s self-worth.
JUDGE AND CABLE
that most organizations desire high productivity, organizational
rewards such as pay level and promotions often are tied, at least in
part, to employees’ productivity on the job (e.g., Barkema &
Gomez-Mejia, 1998; Cleveland, Murphy, & Williams, 1989). In
most firms, employees also receive subjective performance eval-
uations from their managers, thus giving firms the opportunity to
incorporate employee behaviors and attitudes with their objective
job accomplishments (Cleveland et al., 1989). Accordingly, firms
can distribute rewards such as pay level and promotions based on
both objective results (what was accomplished) and subjective
evaluations (how it was accomplished).
General Predictions From Model
We have developed a general theoretical model of the processes
that mediate an individual’s physical height and his or her career
success. Although each path or linkage in the model represents an
avenue for future research, several overarching implications of the
model emerge. As an initial examination of the model, we next
propose some general hypotheses implied by the model that must
be supported if the model is deserving of future research. For
example, although the model does not show a direct link from
height to career success, there is little reason for future researchers
to investigate the proposed mediating linkages between height and
career success if there is not a relationship between the two
variables in the first place (Baron & Kenny, 1986).3Moreover, as
described in the introduction, the three previous studies that have
investigated the height–income relationship may be flawed, be-
cause they investigated initial job offers where height may be
especially relevant (i.e., interviewers may use height as a surrogate
for persuasiveness or even intelligence) rather than studying ca-
reers. Thus, as a preliminary examination of the model, we pro-
Hypothesis 1a: Height is positively related to ascendancy into
Hypothesis 1b: Height is positively related to earnings.
Next, the model suggests several links that mediate the relation-
ships between height and career success, ranging from social- and
self-esteem to performance (i.e., subjective and objective perfor-
mance). Theoretically, the pattern of statistical relationships
should follow this trend, such that the effect of height is greatest on
the most proximal mediators and is smallest with the most distal
mediators (Baron & Kenny, 1986). This logic leads to the follow-
Hypothesis 2: Height exhibits a simplex relationship with
status, performance, and then career success, such that height
is most strongly related to status and least strongly related to
Finally, the logic behind the model indicates that height should
be more strongly related to subjective outcomes (e.g., supervisors’
performance evaluations, leadership effectiveness ratings) than
objective outcomes (e.g., actual sales performance, promotions).
As described earlier, theory suggests that height may play a role in
the workplace because it creates self-fulfilling prophecies and
perceptual biases in judges, including interviewers and supervisors
(Dipboye, 1982). From this vantage point, an employee’s height
should affect perceptions and judgments about performance more
than it affects the employee’s objective job or task performance. In
fact, Hensley and Cooper (1987) suggested that “height is an
important attribute in securing a position but it has little effect on
job performance” (p. 844). Although our proposed model chal-
lenges Hensley and Cooper’s (1987) assertion, the model does
suggest that to the extent that height affects objective performance,
subjective performance ratings are twice affected by height. In
other words, managers’ subjective performance ratings are based
in part on actual performance and in part on self-fulfilling pro-
cesses whereby managers are more likely to attribute greater
performance to taller people (Merton, 1948; Roberts & Herman,
1986). No past research has tried to identify how height affects
objective versus subjective outcomes, so it appears useful to dis-
tinguish between different types of workplace success and to make
the following prediction about the strength of relationships.
Hypothesis 3: Height is more strongly related to subjective
outcomes than objective outcomes.
In the next section of this article, we describe a meta-analysis of
the existing literature and four new investigations that allow us to
test the general hypotheses implied by our theoretical model.
META-ANALYSIS OF RELATIONSHIP BETWEEN
HEIGHT AND WORKPLACE SUCCESS
To identify all possible studies of the relationships between
height and various criteria that indicate success (leadership, per-
formance, status, earnings, income), we searched several databases
(PsycINFO, Social Sciences Abstracts, Sociological Abstracts). In
addition to the electronic searches, we examined the reference lists
of reviews of the literature (Bass, 1990; Hensley & Cooper, 1987;
Roberts & Herman, 1986; Stogdill, 1948). Our searches resulted in
the identification of 71 articles, 44 of which contained correlations
or information that could be translated into correlations. Articles
were excluded for one of four reasons: (a) they were reviews of the
literature, and thus had no original correlations to report; (b) they
did not report statistics on height; (c) they did report statistics on
height, but in such a form that a correlation could not be computed
(percentages, means with no standard deviations, etc.); and (d)
they were deemed inappropriate for other reasons, such as one
study that reported height–income correlations across nations (i.e.,
at the nation level of analysis; Steckel, 1983). A list of studies
included in the meta-analysis is provided in the reference list.
Using Hunter and Schmidt’s (1990) methodology, we corrected
each primary correlation for attenuation due to unreliability, and
then we computed the sample-weighted mean of these corrected
correlations. When height was measured precisely with a physical
3Direct links (e.g., from height to performance or career success) are
certainly possible in the model, but for purposes of simplicity they are not
shown in Figure 1.
EFFECT OF PHYSICAL HEIGHT
examination, we assumed that it was measured perfectly. When
height was estimated, self-reported, or taken from records, we used
Copeland’s (1938) estimate of the average reliability of height in
personnel records (rxx? .87). For the criterion measures, if reli-
ability estimates were reported in the studies, we used these
estimates. For the majority of studies, which did not report reli-
ability estimates, we relied on the literature. We used Viswesvaran,
Ones, and Schmidt’s (1996) estimates for the reliability of super-
visory ratings of job performance and leadership. For objective
measures of job performance, we used Hunter, Schmidt, and
Judiesch’s (1990) estimate of the reliability of objective produc-
tivity measures (ryy? .92; Barrick & Mount, 1991). For perceived
status, we used Haug and Sussman’s (1971) estimate of the cor-
relation (ryy? .74) between the two most widely used measures of
occupational status (thus providing an index of alternative forms
reliability). We made no correction for range restriction.
In addition to reporting point estimates for corrected correla-
tions, we report 80% credibility intervals and 90% confidence
intervals around the estimated population correlations. Confidence
intervals provide an estimate of the variability around the esti-
mated mean corrected correlation; a 90% confidence interval
around a positive point estimate that excludes zero indicates that if
the estimation procedures were repeated a large number of times,
the point estimate would be larger than zero in 95% of the cases.
Credibility intervals provide an estimate of the variability of indi-
vidual correlations across studies; an 80% credibility interval
excluding zero indicates that 90% of the individual correlations in
the meta-analysis excluded zero (for positive correlations, less than
10% are zero or negative). Thus, confidence intervals estimate
variability in the mean correlation, whereas credibility intervals
estimate variability in the individual correlations across the
To test for the presence of moderator effects, as recommended
by Sagie and Koslowsky (1993), we report the Q statistic (Hunter
& Schmidt, 1990, p. 151), which tests for homogeneity in the true
correlations across studies. A significant Q statistic (which is
approximately distributed as a chi-square) indicates the likelihood
of moderators that explain variability in the correlations across
studies. If a significant Q statistic across moderator categories
becomes nonsignificant within a moderator category, it suggests
that the moderator explains a significant amount of the variability
in the correlations across the moderator categories.
Results of the meta-analysis are provided in Table 1. The results
show that, across all criteria, height has an uncorrected correlation
of .22 with the criteria and a corrected correlation of .26. The
confidence interval excludes zero, which indicates that one can be
confident that the average validity of height is nonzero. The
credibility interval also excludes zero, which indicates that more
than 90% of the individual correlations are positive.
Next, Table 1 reports validity broken down by (a) gender of
sample (all male, all female, mixed gender); (b) type of criterion
(social esteem [measures of the perceived status, potential, esteem,
or stature of individuals], leader emergence [election, nomination,
or ranking of individuals in leadership positions], job, task, or
academic performance [objective measures of job performance,
such as sales, academic performance, athletic performance, or
performance ratings]); and (c) measure of the criterion (subjective
Meta-Analysis of Relationship of Height to Success
80% CV 90% CI
Across all criteria
Overall45 7,691 .22.26.20 .01.51.20.32 254.06**
Gender of sample
Type of criterion
Measure of criterion
correlations, because in some studies correlations were reported by moderator category or because the classi-
fication of some criteria was ambiguous (and therefore were excluded). Subjective outcomes included ratings of
performance, ratings of leadership effectiveness, and ratings of social esteem. Objective outcomes of criteria
included objective measures of job performance, earnings, and ascension to formal positions of leadership. k ?
number of correlations; N ? combined sample size; r ? ? estimated average uncorrected correlation; ? ˆ ?
estimated true score correlation; SD? ˆ? standard deviation of estimated true score correlation; CV ? credibility
interval; CI ? confidence interval; Q ? test for homogeneity in the true correlations across studies.
** p ? .01.
The number of correlations within each moderator category does not always match the number of overall
JUDGE AND CABLE
ratings or an extrinsic or objective measure of earnings, perfor-
mance, or attainment). Broken down by gender, results reveal that
height has somewhat higher validity for men (? ˆ ? .29) than for
women (? ˆ ? .21), and the 80% credibility interval includes zero
for women but not for men. On the other hand, the 90% confidence
intervals exclude zero for both men and women, and the difference
in the average correlation is not substantial. To determine whether
the correlations were significantly different, we used the Quin ˜ones,
Ford, and Teachout (1995) Z test. The test revealed that the
difference in the estimated corrected correlation (? ˆ) was not sig-
nificantly different for men and women (Z ? 1.86, ns).
As for the validity broken down by type of criterion, the results
in Table 1 reveal that social esteem (? ˆ ? .41) has the strongest
correlation with height, followed by leadership (? ˆ ? .24) and then
performance (? ˆ ? .18). The mean correlations of all three variables
are distinguishable from zero, which indicates that one can be
confident that the average correlations of height with social es-
teem, leadership, and performance are distinguishable from zero.
The credibility intervals exclude zero for social esteem and per-
formance, but not for leadership, which indicates high variability
in the height–leadership correlations across studies. Thus, these
results generally (on average) support Hypothesis 1a, which states
that height is positively related to the leader emergence aspect of
career success. Again by using the Quin ˜ones et al. (1995) test, we
found that the height–social esteem correlation is significantly
higher than the correlations of height with leader emergence (Z ?
2.40, p ? .01) and performance (Z ? 4.91, p ? .01). These results
provide partial support for Hypothesis 2 (height is more strongly
linked to social esteem than it is to performance or leader emer-
gence), although the data did not reveal predicted differences in the
size of the height–performance versus the height–leader emer-
gence linkages. Finally, in terms of validities by criterion measure
(subjective ratings vs. extrinsic measure), the results show that
subjective ratings (? ˆ ? .31) have higher validity than extrinsic
measures (? ˆ ? .21), and the difference is significant (Z ? 2.17,
p ? .01). Thus, Hypothesis 3 is supported.4
Alhough meta-analysis is a useful means of summarizing results
across studies, the results are limited to bivariate relationships.
Guzzo, Jackson, and Katzell (1987) comment that the failure to
take potential confounds into account is a limitation with meta-
analysis, noting, “A major threat to internal validity is the failure
to account for the possible influences of other variables on the
relationships of interest” (p. 436). We next describe four new
investigations that examine the relationship between height and
income, which links height to a new criterion (earnings) and allows
us to test other aspects of the height effect.
ESTIMATING THE EFFECT OF HEIGHT ON
To increase the validity of the regression estimates with regard
to the effect of height on earnings, we took several control vari-
ables into account.
The average height of Americans is 69.1 in. (175.5 cm) for men
and 63.7 in. (161.7 cm) for women (Body Measurements, 2002), a
difference of more than 5 in. (12.7 cm). The difference between
earnings for men and women is one of the more well-documented
facts in the compensation literature, and inferential studies consis-
tently support gender differences in pay, even after controlling for
other influences (Rynes & Bono, 2000). The reasons for the gender
gap are manifold and complex, although the gap appears to gen-
eralize across nations (Gornick & Jacobs, 1998). Because men and
women differ in both height and earnings, it is possible that gender
may affect the height–income relationship.
Over the life span, individuals lose 1 to 3 in. in their height, with
the average individual losing 5 cm (roughly 2 in.) in height (AGS
Geriatric Review, 2002). Because others may implicitly norm
height by age, we control for age in estimating the effect of height
Obviously, height and weight are correlated, and yet they may
exert effects in opposite directions. Whereas there are many rea-
sons to believe that height has positive effects on status-oriented
variables (Roberts & Herman, 1986), weight may have the oppo-
site effect. In reviewing the literature, Roehling (1999) concluded,
“Overall, the evidence of consistent, significant discrimination
against overweight employees is sobering. Evidence of discrimi-
nation is found at virtually every stage of the employment cycle”
(p. 982). Because failure to distinguish between height and weight
“naturally confounds the interpretation of any effects observed”
(Roberts & Herman, 1986, p. 114), the individual effects of height
and weight need to be isolated.
To maximize the generalizability of the results, we studied the effect of
height on earnings across four unique, complementary samples. The sam-
ples, participants, procedures, and measures are described, study-by-study,
in the following discussion. We restricted the analyses to individuals who
averaged 20 hours or more of work per week, except for Study 1, in which
we restricted the analyses to individuals who were the primary wage
earners in their family.
Sample, Participants, and Procedure
Data for Study 1 were obtained from the Quality of Employment Survey
(QES), a U.S. Department of Labor study of the working conditions of a
4We should note that Figure 1 refers to objective and subjective per-
formance, whereas the results reported in Table 1 (that bear on Hypothesis
3) reference objective criteria (objective measures of job performance,
earnings, and ascension to formal positions of leadership) and subjective
criteria (rated performance, leadership effectiveness, or perceived status)
more generally. Ideally, we would have separated studies by objective and
subjective measures of performance. Unfortunately, there were not enough
studies utilizing each of these measures of performance to conduct separate
meta-analyses. There was only one study that related height to a subjective
measure of job performance in a work setting (Collins, 1955); the other five
studies utilizing subjective measures of performance concerned task per-
formance or performance in an academic setting (e.g., Villimez, Eisenberg,
& Carroll, 1986). For objective measures of performance, the situation was
better, although there still were only eight studies relating height to
objective job performance.
EFFECT OF PHYSICAL HEIGHT
national probability sample of U.S. workers aged 16 and older in 1972–
1973 (Quinn, Mangione, & Seashore, 1975). The University of Michigan
Survey Research Center identified individuals through a national proba-
bility sampling procedure. Data were collected through personal interviews
with individuals at their households. A large amount of data, including
various demographic and personal data, were collected by trained inter-
viewers. The structured interview schedule contained both closed- and
open-ended questions, although for our study only responses to the closed-
ended questions were utilized.
question, “How much does your income from your job figure out to be a
year, before taxes and other deductions are made?” Earnings were adjusted
based on the Consumer Price Index to reflect 2002 U.S. dollars.
Age was measured by asking each individual his or her age in
The interviewer recorded the sex of the respondent, where
1 ? male and 2 ? female.
Height was measured by asking each individual to report his or
her height in inches.
The interviewer evaluated each individual’s weight relative to
his or her height, using a 1 ? obese to 5 ? skinny scale. High scores reflect
being overweight; the variable was reverse-scored so that 1 ? skinny, 2 ?
underweight, 3 ? average for height, 4 ? overweight, and 5 ? obese.
Earnings were measured by the response to the interviewer
Sample, Participants, and Procedure
Data for Study 2 were collected from participants in the National
Longitudinal Surveys (NLS), a continuing project sponsored and directed
by the Bureau of Labor Statistics, U.S. Department of Labor. In 1979, a
longitudinal study of a cohort of young men and women aged 14 to 22 was
begun (NLSY79). The surveys include data about a wide range of events
such as schooling and career transitions, marriage and fertility, training
investments, child-care usage, and drug and alcohol use. The NLSY79 has
had high retention rates; therefore, many NLS survey members have been
monitored for many years, most for decades.
The NLSY79 researchers identified households that were intended to be
representative of the U.S. population. Thus, a national probability sample
was identified; interviewers subsequently visited these households and
performed screening interviews. The vast majority (87%) of individuals in
visited households participated in the study. Most of the data were col-
lected via personal interviews. From 1979–1993, individuals were inter-
viewed every year. Since 1994, individuals were interviewed every other
year. The last interview for which data are available took place in 2000.
NLSY79 participants live in all 50 states and the District of Columbia.
their income from wages and salary. To increase the reliability of this
variable and take advantage of the fact that this question was asked over
time, one variable was created that reflected average earnings from 1985–
2000 (? ? .92). Earnings were adjusted based on the Consumer Price
Index inflation index to reflect 2002 U.S. dollars.
Age was measured with a question on the 2000 interview that
asked the individual to report his or her age in years.
Gender was measured by a question on the original 1979
survey that asked the interviewer to record the gender of the individual.
Gender was coded 1 ? male, 2 ? female.
Earnings were measured by asking individuals to report
sured in inches. To form the most reliable measurement, height was
measured as the average height reported in 1981 and 1985 (? ? .97).
Weight was the self-reported weight of the individual as of
1985, reported in pounds.
Height was the self-reported height of the individual, mea-
Sample, Participants, and Procedure
The data for this study were obtained from the Intergenerational Studies,
administered by the Institute of Human Development, University of Cali-
fornia at Berkeley. The Intergenerational Studies are a combination of the
following three longitudinal studies commissioned by the Institute in the
1920s: (a) the Berkeley Guidance Study enrolled children born in Berkeley,
California, from January 1928 to July 1929; (2) the Berkeley Growth Study
enrolled children through area pediatricians and obstetricians and included
infants born between January 1928 and May 1929 (given the time frame,
there was some overlap with the Guidance sample, although most Guid-
ance study members were born at home); and (c) the Oakland Growth
Study, initiated in 1931, recruited children from five elementary schools in
Oakland. There were three major follow-up studies, completed when
participants were 30–38 (early adulthood), 41–50 (middle age), and 53–62
(late adulthood) years old. In these follow-up studies, participants were
intensively interviewed about their work and family lives. Because essen-
tially the same measures were collected in the three studies, they were
combined in the analyses.
average individual was 41–50 years old) with an interview question that
asked the individual to report his or her annual pretax earnings. Responses
were placed in the following categories: 1 ? less than $15,000, 2 ?
$15,000–$19,999, 3 ? $20,000–$29,999, 4 ? $30,000–$39,999, 5 ?
$40,000–$49,999, and 5 ? $50,000 and over. This variable was standard-
ized prior to analysis.
Age was measured by the interviewer asking individuals to report
their age. At the time of the interview, individuals’ ages ranged from 29 to
Gender of the individual was recorded at the onset of the
study, when individuals were entered into the study at birth. Individuals’
gender was originally coded as part of their identification number where
M ? male (57%) and F ? female (43%). These alphanumeric codes were
translated so that 1 ? male and 2 ? female.
Height was measured as a result of an examination adminis-
tered by a physician when the individuals were, on average, in their 30s.
Height measurements were made in centimeters and were converted into
Weight was measured as part of the same physical examina-
tion. Individuals’ weight was measured with a scale and was coded in
kilograms and converted into pounds.
Total earnings were measured at the Adult 2 stage (when the
Sample, Participants, and Procedure
Participants were individuals from Great Britain’s National Child De-
velopment Study (NCDS), a birth cohort survey that followed individuals
who were born in Great Britain from March 3–9, 1958. The initial data
collection focused on the newborn children and their parents. Since that
time, there have been five follow-up interviews: 1965, 1969, 1974, 1981,
and 1991. In 1991, individuals were 33 years old. The NCDS has gathered
data from respondents on child development from birth to early adoles-
cence, including such diverse areas as child care, health, physical statistics,
JUDGE AND CABLE
home environment, parental involvement, economic activity, income, and
housing. Data were collected using diverse methodologies, including in-
terviews, questionnaires, parental interviews, and medical examinations.
sessed the individuals’ current earnings per hour. The variable was trans-
formed to reflect yearly earnings. Earnings were converted from British
pounds to U.S. dollars and then were adjusted based on the Consumer Price
Index to reflect 2002 dollars.
Gender was recorded at the commencement of the study and
was coded 1 ? male, 2 ? female.
Height was measured by averaging the height measurements at
age 16 and age 23 (? ? .93), during which individuals’ height was
measured by a local authority medical officer. Height was measured in
centimeters, which we subsequently converted into inches.
Weight was measured by averaging the weight measures at
age 16 and age 23 (? ? .81). As with height, weight was measured by a
local authority medical officer during individuals’ medical examinations.
Weight was measured in kilograms and was subsequently converted into
Earnings were measured in 1991 with a variable that as-
Descriptive statistics and correlations among the study variables
are provided in Tables 2 and 3. As is shown in Tables 2 and 3,
height was significantly positively correlated with earnings in all
four samples. The height–earnings correlations were relatively
consistent, ranging from r ? .24 to r ? .35 (all ps ? .01).
The regression results—using height, weight, age, and gender to
predict earnings—are provided in Table 4. For Study 1, the re-
gression results reveal that age (? ? .15, p ? .05) and height (? ?
.20, p ? .01) positively predict earnings. The multiple correlation
for the regression is R ? .31 and R2? .09 (p ? .01). For Study
2, gender negatively predicts earnings such that women earn less
than men (? ? -.20, p ? .01). Age positively predicts earnings
(? ? .13, p ? .01) and weight negatively predicts earnings (? ?
-.06, p ? .01). Height positively predicts earnings (? ? .20, p ?
.01). The multiple correlation is .35, and the independent variables
explain 13% of the variance in earnings. For Study 3, height
significantly predicts earnings (? ? .44, p ? .01). The multiple
correlation is R ? .38 (p ? .01), and on average the independent
variables explain 15% of the variance in earnings. Finally, in Study
4, gender (? ? -.17, p ? .01), weight (? ? -.06, p ? .01), and
height (? ? .18, p ? .01) each significantly predict earnings. The
multiple correlation is R ? .29 (p ? .01), and the independent
variables explain 8% of the variance in earnings. Overall, the
results are quite consistent with respect to the effect of height on
earnings in that, across all four studies, height significantly pre-
dicted earnings with ?s ranging from .18 to .44. Thus, Hypothesis
1b is supported.
In addition to the standardized regression (?) coefficients re-
ported in Table 4, the results revealed that the unstandardized
regression (B) coefficients have appreciable effect sizes. The un-
standardized coefficient estimates reveal that each inch increase in
height results in a predicted increase in annual earnings of $897 in
Study 1, $728 in Study 2, and $743 in Study 4 (it was not possible
to obtain effect size estimates for Study 3 given that salary was
coded into categories). By averaging across these results, we find
that an individual who is 72 in. tall could be expected to earn
$5,525 more per year than someone who is 65 in. tall, even after
controlling for gender, weight, and age.
One advantage of the four height–earnings studies over the
meta-analysis is the ability to conduct more detailed analyses to
uncover boundary conditions. Thus, we next examine the role of
gender, intelligence, time, and occupation in the relationship be-
tween physical height and earnings.
Differential Effects by Gender
It has been speculated that the efficacy of height may be differ-
ent for men and women. Specifically, Hensley and Cooper (1987)
cautioned that height may be advantageous for men only, and
Frieze and colleagues (1990) comment that, compared to men, tall
women may be more apt to be seen as “too tall” (p. 48). Although
the regression analyses that predict earnings with height control for
gender, they do not address whether there is differential validity by
gender. To investigate whether the validity of height varies for
men and women, we conducted three types of analyses. First,
descriptively, we calculated the average salary (M$) of men and
women ?1 standard deviation (SD) beyond the mean in height. In
Study 1, for men ?1 SD in height (height ? 72.6 in.), M$?
$60,229; for men –1 SD in height (height ? 67.38 in.), M$?
$48,407; for women ?1 SD in height (height ? 66.88 in.), M$?
$29,533; for women –1 SD in height (height ? 62.14 in.), M$?
$24,028. In Study 2, for men ?1 SD in height (height ? 72.99 in.),
M$? $70,835; for men –1 SD in height (height ? 66.97 in.),
M$? $52,704; for women ?1 SD in height (height ? 66.87 in.),
M$? $42,425; for women –1 SD in height (height ? 61.49 in.),
M$? $32,613. In Study 4, for men ?1 SD in height (height ?
71.23 in.), M$? $42,726; for men –1 SD in height (height ? 65.77
Means (M), Standard Deviations (SD), and Intercorrelations Among Study 1 and Study 2 Variables
4. Height (in inches)
5. Earnings (U.S. dollars)
48,247.52 33,850.18 38,272.26
is coded as 1 ? male, 2 ? female. For Study 1, weight was coded on a 1 ? skinny to 5 ? obese scale. For Study 2, weight is in pounds. Earnings were
adjusted to reflect 2002 dollars.
** p ? .01, two-tailed.
Correlations for Study 1 (listwise n ? 261) are below the diagonal. Correlations for Study 2 (listwise n ? 4,314) are above the diagonal. Gender
EFFECT OF PHYSICAL HEIGHT
in.), M$? $38,913; for women ?1 SD in height (height ? 66.13
in.), M$? $35,825; for women –1 SD in height (height ? 61.17
in.), M$? $30,823. With the exception of Study 4, these results
show somewhat greater height effects for men than women, al-
though the proportional or percentage gender differences are
Second, we estimated height–earnings relationships for men
and women separately and then used Fisher’s r-to-Z transforma-
tion to test the “male”and “female” correlations for significance. In
no case, across the four studies, was the height–earnings correla-
tion significantly different for men and women. Furthermore, the
absolute value of the difference was relatively small (r ? .05).
We also tested differential validity by gender using hierarchical
moderated regression. The incremental R2values, when the inter-
action was added to the regression, were very small and nonsig-
nificant across the four studies: Study 1, ?R2? .007 (ns); Study 2,
?R2? .001 (ns); Study 3, ?R2? .002 (ns); and Study 4, ?R2?
.001 (ns). Thus, not only does height affect earnings controlling for
gender, its effect appears to operate similarly for men and women.
This result is concordant with the earlier meta-analytic results,
where the average validity of height was not significantly different
between the genders.
Role of Intelligence
It has been speculated that height and intelligence are positively
related (Roberts & Herman, 1986), and therefore the reason tall
people appear to have an advantage is really due to greater intel-
lect. In Study 3, intelligence and height were indeed significantly
correlated (r ? .26, p ? .01). However, controlling for intelligence
did not affect the relationship of height with earnings. The stan-
dardized regression coefficient of height in predicting earnings
changed from ? ? .44 to ? ? .42 when controlling for intelli-
gence. On the other hand, for the participants in Study 2 for whom
intelligence test scores were available, intelligence had no rela-
tionship with height (r ? -.05, ns) or earnings (r ? .08, ns). Thus,
contrary to the speculation of some researchers, it does not appear
that the advantages of height are due to a possible link between
height and intelligence.
Does the Height Effect Decline Over Time?
Research has suggested that the validity of individual differ-
ences may decline over time, as the interval between the measure-
ment of the individual difference and the criterion increases (Hu-
lin, Henry, & Noon, 1990). Thus, to better understand the
psychosocial implications of height, it is important to ascertain
whether the validity of height declines over time. Specifically, is it
most useful to be tall early in one’s career, and do the advantages
wane once the individual has acquired more job-relevant human
capital? To investigate this possibility, we used data from Study 2,
which contained the best information on earnings over time. In
correlating height with income, the following correlations were
observed by year: 1985, r ? .23, N ? 10,471; 1986, r ? .24, N ?
10,100; 1987, r ? .25, N ? 9,800; 1988, r ? .27, N ? 9,828; 1990,
r ? .25, N ? 9,684; 1991, r ? .26, N ? 8,401; 1993, r ? .26, N ?
8,161; 1994, r ? .27, N ? 8,049; 1996, r ? .26, N ? 7,868; 1998,
r ? .28, N ? 7,559; 2000, r ? .26, N ? 7,236. The results show
that the validity of height in predicting earnings does not decline
over time. If anything, there is a very slight upward trend in the
Does the Validity of Height Vary by Occupation?
According to the theoretical model, height affects career suc-
cess, in part, because it affects individuals’ social esteem, which in
turn helps increase performance. From this perspective, the effect
of height on earnings should be greater in occupations where
stature and respect of others matter more. One way to investigate
whether height is more relevant for more social occupations is to
correlate height with income within occupational categories. Ac-
cordingly, again using Study 2 because it had the most complete
occupational breakdowns, we correlated height and income based
on the occupational breakdowns provided in the NLS database.
The results of this correlational analysis are provided in Table 5. In
general, the results are consistent with the proposition that in social
Means (M), Standard Deviations (SD), and Intercorrelations Among Study 3 and Study 4 Variables
3. Weight (in lbs.)
4. Height (in inches)
5. Earnings (in U.S. dollars)
is not included in Study 4 because all individuals are the same age (within 3 weeks). Gender is coded as 1 ? male, 2 ? female.
** p ? .01, two-tailed.
Correlations for Study 3 (listwise n ? 118) are below the diagonal. Correlations for Study 4 (listwise n ? 3,872) are listed above the diagonal. Age
Relationship of Height to Earnings: Studies 1–4
VariableStudy 1Study 2 Study 3Study 4
regression (?) coefficients not corrected for the effects of measurement
* p ? .05. ** p ? .01.
With the exception or R, R2, and N, table entries are standardized
JUDGE AND CABLE
interaction-oriented occupations— occupations that may rely on
appearance and stature as a means of achieving success— height is
more predictive of earnings. Specifically, height was correlated
(r ? .41, p ? .01) with earnings in sales and in management (r ?
.35, p ? .01). Height also was less valid in less social occupations,
although height was slightly more predictive of earnings in blue-
collar occupations (r ? .32, p ? .01) than in professional-technical
occupations (r ? .30, p ? .01). It is worth noting that many
professional-technical occupations (e.g., metallurgists, engineers,
technicians, computer programmers) may not be particularly
stature- or appearance-oriented. Finally, although height is gener-
ally less predictive of earnings in less social occupations, the
validity of height does not entirely disappear. Height is moderately
correlated with earnings even in clerical (r ? .25, p ? .01) and
craft (r ? .24, p ? .01) occupations. As with gender, we also tested
whether height varies by occupation by computing an interaction
between height and a dummy variable for each occupation and
then entering the interaction in regressions predicting earnings.
The incremental variance explained was relatively small (ranging
from .003 [p ? .01] for professional-technical occupations to .017
[p ? .01] for blue-collar occupations), although the interaction was
not significant in only one case, with sales occupations (?R2?
We live in a society where physical appearance matters, not only
because it affects how others respond to us but it also affects how
we view ourselves. Physical traits clearly play an important role in
workplace interactions and outcomes, and there is active literature
that focuses on how attractiveness, weight, and body image affect
workplace interactions and outcomes (e.g., DeGroot & Motowidlo,
1999; Gilmore, 1986; McElroy, 1999; Pingitore, Dugoni, & Tin-
dale, 1994; Roehling, 1999; Trethewey, 1999).
The present article focused on one of the most obvious aspects
of appearance—physical height—and its role in workplace suc-
cess. Many people are aware of the Napoleon complex and have
considered the possibility that height, personality, and behavior
may be connected. Although there are decades of empirical re-
search on the topic of height in the workplace, the research has
been infrequent and sporadic, and there has been little serious
inquiry regarding this topic since the early 1980s. Moreover,
results from studies that are conducted often are greeted with a
mixture of skepticism and humor by scholars (Keyes, 1980). As
Hensley and Cooper (1987) noted in their review of the height–
success literature: “While these accounts may draw an amused
readership they remain matters of speculation, not science” (p.
844). The haphazard treatment of the height–workplace success
topic may be due, in part, to researchers’ unwillingness to believe
that such a nonperformance-related attribute could play much of a
role in performance-oriented environments. However, as Prieto
and Robbins (1975) suggested, “Since it can be demonstrated that
this culture positively values tall stature, particularly for males,
reflected in most advertising, fashion design, athletics, occupa-
tional qualifications, leadership, social status, and heterosexual
relationships, the consequences of short stature deserve attention
from behavioural scientists” (p. 395).
In the present study, we developed a theoretical model of the
relationship between physical height and career success, both as a
mechanism to draw together existing investigations and as a
framework to provide direction for future research in this area. To
test some of the general implications of the theoretical model, we
then conducted a meta-analysis of the existing literature, and we
complemented the meta-analysis with four primary investigations
of the linkage between physical height and salary.
First, and perhaps most important, results from our analyses
revealed that height clearly matters in the context of workplace
success. The overall meta-analytic results, based on 45 indepen-
dent studies, demonstrated that height has a non-zero association
with success (? ˆ ? .26). Height also was significantly and posi-
tively related to earnings in all four of our earnings studies,
controlling for sex, age, and weight. In fact, a meta-analysis of our
four earnings studies suggested a mean sample-size–weighted va-
lidity of .31. Moreover, the unstandardized coefficients suggested
that an individual who is 72 in. tall would be predicted to earn
almost $166,000 more across a 30-year career than an individual
who is 65 in. tall. Our analysis in Study 2 revealed that the effect
of height appears to be quite stable over the course of one’s career;
height does not appear to be an ephemeral advantage that matters
only early in life and then dissipates. In general, the combined
results presented in this article suggest important, meaningful
differences in workplace success depending on physical height.
Thus, one important takeaway from this investigation is that the
topic of physical height deserves equal footing with other types of
physical attributes that garner serious scholarly attention, such as
attractiveness and weight.
Moreover, the positive pattern of results revealed by both the
meta-analysis and the income studies questions the conclusions of
past qualitative reviews of the height–success literature. Specifi-
cally, past reviews of the literature have suggested that height
affects societal markers of status or success but not actual perfor-
mance on the job. For example, Hensley and Cooper (1987) noted,
“Height is an important attribute in securing a position but it has
little effect on job performance” (p. 844), while Hensley and
Angoli (1980) suggested, “Perceptual distortion of height is a
diminishing occurrence with the magnitude dampening over time
with increased interaction” (p. 154). Likewise, Hensley (1993)
noted, “There is no evidence that height leads to enhanced job
performance” (p. 40).
Height–Income Correlations by Occupation: Study 2
occupational sample sizes because occupational groups with small num-
bers of individuals (farmers and armed forces, n ? 10) were excluded.
** p ? .01, two-tailed.
The overall sample size does not equal the sum of the rest of the
EFFECT OF PHYSICAL HEIGHT
Although there may be overlap between subjective and objec-
tive job performance, the results from our meta-analysis suggest
that height may indeed be related to objective performance, al-
though not as strongly as it is related to social esteem or subjective
criteria. Specifically, the evidence suggested that height was more
predictive of subjective ratings (? ˆ ? .31) than objective outcomes
(? ˆ ? .21). Thus, consistent with the model, height seems to predict
how observers perceive and evaluate others more than it predicts
actual performance. Even in the case of objective outcomes, how-
ever, the validity of height was comparable to other bellwether
predictors of job performance, such as the personality trait of
conscientiousness (Hurtz & Donovan, 2000). Although future re-
search clearly is needed, this evidence helps demonstrate the value
of empirical, meta-analytic investigations of research literature in
addition to qualitative reviews of trends (e.g., Cooper & Rosenthal,
At one time, height was explicitly considered in hiring decisions
(Otis, 1941). What was once explicit may now be implicit, but
height nonetheless continues to be a factor in terms of promotions
and decisions about pay. In a normative sense, these findings are
troubling in that, with the exception of a few occupations (e.g.,
professional basketball), height cannot be considered an essential
ability required for job performance nor a bona fide occupational
qualification (BFOQ). Thus, there probably are many types of jobs
where the practice of favoring tall individuals amounts to little
more than pure bias, such as construction work or back-office
professional services (e.g., accounting or legal services). However,
the role of height in other types of positions may be somewhere
between pure bias and BFOQ, whereby height affects customer
decisions and thus affects individual performance and subsequent
career success. Thus, in some jobs tall people may have higher
levels of performance and career success because customers or
other constituents may view them more positively (Frieze et al.,
1990). In fact, some initial evidence for this possibility was sug-
gested by our occupational analysis (see Table 5), which indicated
greater linkages between height and earnings in occupations where
persuasion and negotiation are more critical (e.g., sales, manage-
ment). Future research is needed to indicate more clearly what jobs
benefit from height and the processes through which height affects
success on those jobs.
It also is interesting to consider Adler’s (1956) concept of the
Napoleon complex in the context of the workplace. To the extent
that some short individuals overcompensate for their lack of stat-
ure with overaggressive, belligerent, or arrogant actions (e.g.,
Dollard, Doob, Miller, Mowrer, & Sears, 1939), it is possible that
aggression may mediate the relationship between height and work-
place success. Although one study (Willoughby & Blount, 1985)
did reveal that shorter police officers displayed more aggressive
behavior than taller officers, there is almost no empirical data on
the height–aggressiveness relationship. More research is needed on
Finally, our results suggest that it is not simply the case that
height operates as a proxy for gender, even though men are on
average taller than women. Indeed, the results of four earnings
studies show that whereas height and gender are correlated, it
appears that height has a more important effect on earnings than
gender. However, it is likely that firms making human resource
decisions based on height will experience disparate impact, given
the strong relationship between height and sex (average r ? .65),
and therefore may expose themselves to legal threats.
LIMITATIONS AND STRENGTHS
The research reported here has several limitations that should be
noted. First, the overall goal of this article was to open a serious
line of scientific inquiry about why height matters in the workplace
by developing a general theoretical model of how height influ-
ences career success. Although we were able to test some of the
general implications of the model and thus demonstrate the im-
portance of the height–workplace success topic, this study does not
open the black box between height and workplace success. Future
research is needed to investigate the specific mediating processes
described in the model, which lead from physical height to social
and self-esteem, performance, and career success.
Another limitation is that our meta-analysis inherits the short-
comings of the literature that it summarizes. For example, some of
the studies in the literature suggest that demand cues may have
existed when the predictor and outcome variables were perceptual
and collected together (Roberts & Herman, 1986). To the extent
that respondents reported a person’s height and then judged the
person’s performance, “it is hard to imagine subjects not coming to
an accurate estimation of the hypothesis being tested” (Roberts &
Herman, 1986, p. 134). Although this concern is offset by similar
relationships between height and objective criteria, future research
is needed to confirm that the validity differences between objective
and subjective outcomes are not due to methodological artifacts.
Another limitation in the height–workplace success literature is
that much past research on this topic has focused on three occu-
pations: police work, academia, and sales (Roberts & Herman,
1986). This limited range of occupations weakens the generaliz-
ability of the meta-analytic findings.
Finally, the small number of existing studies on the linkages
between height and self-esteem, objective job performance, and
subjective job performance limited our ability to examine these
relationships in our meta-analysis. For example, although we ex-
amined how height relates to objective versus subjective outcomes
in this article, it is important for future research to directly study
how height affects employees’ behaviors and job performance
versus how they are perceived by managers and how these link-
ages vary by occupation.
These limitations are countered by a number of strengths. First,
we developed a general theoretical model of how and why height
influences career success. Because this type of overarching frame-
work was not available in the literature, it was challenging to draw
existing studies together coherently, and it was difficult to see how
new studies could be conducted to build upon the literature. We
hope that this model will further understanding of the role of
height and will pave the way for future studies.
Next, as the first empirical examination of the literature on
height and workplace success, this article offers important infor-
mation about the robustness of effects across many different meth-
odological contexts and outcomes. Thus, our investigation reveals
the general strength and variability of the relationships, which is
useful because trends in research are difficult to interpret.
The studies on earnings also have methodological advantages.
First, height was measured in diverse ways across the four com-
plementary studies, and the relationships between height and in-
JUDGE AND CABLE
come were similar for self-reported versus other-recorded height.
Second, in most cases, height was measured well before earnings
were measured, therefore addressing a limitation in past research
that height and the criteria “are measured almost simultaneously”
(Roberts & Herman, 1986, p. 134). Finally, unlike past research
that has focused on police work, academia, and sales, the four
studies in this manuscript represented the full range of occupations
and offer support for the generalizability of the height–success
Theoretically, it is important to understand how and why phys-
ical height affects people’s success in the workplace. Practically, it
is important for managers to know whether height affects perfor-
mance because it proxies self-confidence and persuasiveness or
whether height acts independently of these processes. The studies
presented in this article clearly suggest that physical height affects
people’s careers and workplace interactions and therefore is wor-
thy of continued scholarly investigation.
References marked with an asterisk indicate studies included in the
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Received November 26, 2002
Revision received June 18, 2003
Accepted July 10, 2003 ?
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